Achieving Rapport with Turn-by-Turn, User-Responsive Emotional Coloring

People in dialog use a rich set of nonverbal behaviors, including variations in the prosody of their utterances. Such behaviors, often emotion-related, call for appropriate responses, but today’s spoken dialog systems lack the ability to do this. Recent work has shown how to recognize user emotions from prosody and how to express system-side emotions with prosody, but demonstrations of how to combine these functions to improve the user experience have been lacking. Working with a corpus of conversations with students about graduate school, we analyzed the emotional states of the interlocutors, utterance by utterance, using three dimensions: activation, evaluation, and power. We found that the emotional coloring of the speaker’s utterance could be predicted from the emotion shown by her interlocutor in the immediately previous utterance. This finding enabled us to build Gracie, the first spoken dialog system that recognizes a user’s emotional state and gives a response with appropriate emotional coloring. Evaluation with 36 subjects showed that they felt significantly more rapport with Gracie than with either of two controls. This shows that dialog systems can tap into this important level of interpersonal interaction using today’s technology

Sistemas de diálogo: una revisión

Spoken dialogue systems are computer programs developed to interact with users employing speech in order to provide them with specific automated services. The interaction is carried out by means of dialogue turns, which in many studies available in the literature, researchers aim to make as similar as possible to those between humans in terms of naturalness, intelligence and affective content. In this paper we describe the fundaments of these systems including the main technologies employed for their development. We also present an evolution of this technology and discuss some current applications. Moreover, we discuss development paradigms, including scripting languages and the development of conversational interfaces for mobile apps. The correct modelling of the user is a key aspect of this technology. This is why we also describe affective, personality and contextual models. Finally, we address some current research trends in terms of verbal communication, multimodal interaction and dialogue management.Los sistemas de diálogo son programas de ordenador desarrollados para interaccionar con los usuarios mediante habla, con la finalidad de proporcionarles servicios automatizados. La interacción se lleva a cabo mediante turnos de un tipo de diálogo que, en muchos estudios existentes en la literatura, los investigadores intentan que se parezca lo más posible al diálogo real que se lleva a cabo entre las personas en lo que se refiere a naturalidad, inteligencia y contenido afectivo. En este artículo describimos los fundamentos de esta tecnología, incluyendo las tecnologías básicas que se utilizan para implementar este tipo de sistemas. También presentamos una evolución de la tecnología y comentamos algunas aplicaciones actuales. Asimismo, describimos paradigmas de interacción, incluyendo lenguajes de script y desarrollo de interfaces conversacionales para aplicaciones móviles. Un aspecto clave de esta tecnología consiste en realizar un correcto modelado del usuario. Por este motivo, discutimos diversos modelos afectivos, de personalidad y contextuales. Finalmente, comentamos algunas líneas de investigación actuales relacionadas con la comunicación verbal, interacción multimodal y gestión del diálogo

Producing Acoustic-Prosodic Entrainment in a Robotic Learning Companion to Build Learner Rapport

abstract: With advances in automatic speech recognition, spoken dialogue systems are assuming increasingly social roles. There is a growing need for these systems to be socially responsive, capable of building rapport with users. In human-human interactions, rapport is critical to patient-doctor communication, conflict resolution, educational interactions, and social engagement. Rapport between people promotes successful collaboration, motivation, and task success. Dialogue systems which can build rapport with their user may produce similar effects, personalizing interactions to create better outcomes. This dissertation focuses on how dialogue systems can build rapport utilizing acoustic-prosodic entrainment. Acoustic-prosodic entrainment occurs when individuals adapt their acoustic-prosodic features of speech, such as tone of voice or loudness, to one another over the course of a conversation. Correlated with liking and task success, a dialogue system which entrains may enhance rapport. Entrainment, however, is very challenging to model. People entrain on different features in many ways and how to design entrainment to build rapport is unclear. The first goal of this dissertation is to explore how acoustic-prosodic entrainment can be modeled to build rapport. Towards this goal, this work presents a series of studies comparing, evaluating, and iterating on the design of entrainment, motivated and informed by human-human dialogue. These models of entrainment are implemented in the dialogue system of a robotic learning companion. Learning companions are educational agents that engage students socially to increase motivation and facilitate learning. As a learning companion’s ability to be socially responsive increases, so do vital learning outcomes. A second goal of this dissertation is to explore the effects of entrainment on concrete outcomes such as learning in interactions with robotic learning companions. This dissertation results in contributions both technical and theoretical. Technical contributions include a robust and modular dialogue system capable of producing prosodic entrainment and other socially-responsive behavior. One of the first systems of its kind, the results demonstrate that an entraining, social learning companion can positively build rapport and increase learning. This dissertation provides support for exploring phenomena like entrainment to enhance factors such as rapport and learning and provides a platform with which to explore these phenomena in future work.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Affective Expressions in Conversational Agents for Learning Environments: Effects of curiosity, humour, and expressive auditory gestures

Conversational agents -- systems that imitate natural language discourse -- are becoming an increasingly prevalent human-computer interface, being employed in various domains including healthcare, customer service, and education. In education, conversational agents, also known as pedagogical agents, can be used to encourage interaction; which is considered crucial for the learning process. Though pedagogical agents have been designed for learners of diverse age groups and subject matter, they retain the overarching goal of eliciting learning outcomes, which can be broken down into cognitive, skill-based, and affective outcomes. Motivation is a particularly important affective outcome, as it can influence what, when, and how we learn. Understanding, supporting, and designing for motivation is therefore of great importance for the advancement of learning technologies. This thesis investigates how pedagogical agents can promote motivation in learners. Prior research has explored various features of the design of pedagogical agents and what effects they have on learning outcomes, and suggests that agents using social cues can adapt the learning environment to enhance both affective and cognitive outcomes. One social cue that is suggested to be of importance for enhancing learner motivation is the expression or simulation of affect in the agent. Informed by research and theory across multiple domains, three affective expressions are investigated: curiosity, humour, and expressive auditory gestures -- each aimed at enhancing motivation by adapting the learning environment in different ways, i.e., eliciting contagion effects, creating a positive learning experience, and strengthening the learner-agent relationship, respectively. Three studies are presented in which each expression was implemented in a separate type of agent: physically-embodied, text-based, and voice-based; with all agents taking on the role of a companion or less knowledgeable peer to the learner. The overall focus is on how each expression can be displayed, what the effects are on perception of the agent, and how it influences behaviour and learning outcomes. The studies result in theoretical contributions that add to our understanding of conversational agent design for learning environments. The findings provide support for: the simulation of curiosity, the use of certain humour styles, and the addition of expressive auditory gestures, in enhancing motivation in learners interacting with conversational agents; as well as indicating a need for further exploration of these strategies in future work

Testing Matching and Mirroring With Homophily in Onboarding Leadership Socialization

This study was designed to test the relationship between matching and mirroring (MM) and homophilous perceptions (PHM) in leadership socialization. Elevated PHM levels were hypothesized to affect workplace acceptance levels. The need for testing leadership socialization skills was magnified with the current demographic shift known as the leadership succession crisis, creating problems with onboarding strategies. The theoretical foundations of the study were based on the social identity theory, the social presence theory, the leader-member exchange theory, and the similarity-attraction paradigm. The study conducted at Workforce Solutions North Texas in Wichita Falls, Texas was sampled based on the calculated strength of the effect in a pilot study. Test group participants engaged in MM enhanced social conversation with a coached candidate and control group participants conversed with an uncoached participant from the general population engaging in normal conversation. MM processes were differentiated from natural synchronic tendencies using specialized software and Kinect-® sensors. A contrasted group, quasi-experiment was examined with an analysis of covariance. No statistically significant difference was found between groups on PHM levels, correcting for age, gender, ethnicity, height, glasses, hobbies, and professions. However, PHM and coworker acceptance were statistically significant but with no difference between groups. Further research is needed to test PHM as a metric for rapport in socialization strategies. Nevertheless, the homophily lens rather than the rapport lens can help organizational development and human resource professionals quantify and develop more effective socialization strategies aimed at solving problems associated with the leadership succession crisis

Studies on Diversification of Speech Expressions for Conversational Speech Synthesis

早大学位記番号:新9251博士（工学）早稲田大